I am a Software Engineer at Bemol, a Brazilian retail company, working in the Backoffice sector focused on improving employee productivity and efficiency. Computer Engineering graduate from Universidade do Estado do Amazonas (UEA) with a strong focus on cutting-edge technologies. Experienced in leveraging Machine Learning, Robotic Process Automation (RPA), Data Analysis, and Embedded Systems, particularly with Arduino and Raspberry Pi. Proficient in Python, with expertise in developing and implementing Machine Learning algorithms, automating tasks, and adept at rapidly acquiring new skills. Known for my ability to effectively communicate and share knowledge within teams.
Python
AWS
- Engaged in a project centered around facial recognition, as I had a final work on my graduation related to it.
- One of the first members of the Robotic Process Automation (RPA) Center of Excellence, being a instructor and coder to a lot of processes within the company, of very different sectors, thus saving hundreds of repetitive work hours in many sectors of Bemol;
- Data analysis related to various projects, like the facial recognition project and SMS providers;
Started as Digital Trainee, quickly advancing to spearhead automation initiatives and act as a liaison between the Fiscal Team and Data Team. Promoted to Software Engineer I, contributing significantly to projects within Bemol Digital. Currently deeply involved in a groundbreaking facial recognition project.
Key responsibilities
• Currently part of a cutting-edge facial recognition project, which consists in recognizing people on the cashiers, reducing attendance time from 18 seconds to 4 seconds, and also helping to detect fraudsters in the store, improving security for managers and employees.
• Contributed significantly to data analysis projects related to SMS, providing valuable insights for the organization, helping them to select the better provider and saving budget.
• Led initiatives within the Robotic Process Automation (RPA) Center of Excellence to streamline processes, helping fellow coworkers on automating and saving time in long processes.
• While a Digital Trainee at the Fiscal Team, automated more than 10 tax reports, improving efficiency and accuracy.
Key achievement/projects
• Attendance time on cashiers reduced from 18 seconds to 4 seconds.
• Security improved for the company to avoid action by fraudsters on cashiers.
• Happiness and satisfaction of managers and cashiers improved.
• Delivery of tax reports for the Fiscal Team improved.
• Sectors of company like HR, Fiscal, Con
Trained neural network models for weather/flooding prediction using real sensor data and built a rulebased fire prevention system with fuzzy logic for Samsung datacenters with real-time anomaly detection pipelines